Hyo Seon Park 교수

Optimization of large structures consisting of thousands of members subjected to the highly nonlinear constraints of the actual commonly used design codes, such as the American Institute of Steel Construction (AISC), Allowable Stress Design (ASD), or Load and Resistance Factor Design (LRFD) specifications (AISC 1989, 1994), requires high-performance computing resources. We have previously developed parallel optimization algorithms on shared memory multiprocessors where a few powerful processors

Neurocomputing for Design Automation provides innovative design theories and computational models with two broad objectives: automation and optimization.This singular book:Presents an introduction to the automation and optimization of engineering design of complex engineering systems using neural network computingOutlines new computational models and paradigms for automating the complex process of design for unique engineering systems, such as steel highrise building structuresApplies design the

Abstract A new monitoring system using GPS is introduced to measure wind‐induced responses of high‐rise buildings. In this paper, wind‐induced responses of a long‐period structure include relative lateral displacements, acceleration records, and torsional displacements at the top of a building. After comparing responses of a test model measured by GPS with responses obtained by the most commonly used laser displacement meters and accelerometers, the wind‐induced responses of a 66‐story high‐rise

In this paper, we propose an efficient puncturing method for LDPC codes. The proposed algorithm provides the order of variable nodes for puncturing based on the proposed cost function. The proposed cost function tries to maximize the minimum reliability among those provided from all check nodes. Also, it tries to allocate survived check nodes evenly to all punctured variable nodes. Furthermore, the proposed algorithm prevents the formation of a stopping set from the punctured variable nodes even